In this work, we propose a symbol-based dpd optimization algorithm using ota observations. Instead of using a sample-based criterion that minimizes the error between oversampled signals, the proposed algorithm minimizes the cross-entropy between transmitted and received symbols. Using the policy gradient theorem [1]}, we generalize the work [2]} by connecting the symbol-based criterion with the sample-based policy optimization, which allows to optimize DPD parameters at the sample level. For a gmp pa and awgn channel, we show that the proposed symbol-based dpd optimization algorithm achieves ser gains over the ila-based dpd optimization algorithm [3]} even with full-rate adc. Error spectrum results show that, although the DPD optimized by the symbol-based criterion focuses more on reducing the in-band errors (i.e., symbol errors), out-of-band errors are still at a satisfactory level.
